My last post generated a few comments from readers out there who disagreed with some of my assessments, and I wanted to start off today by mentioning that I appreciate hearing other people’s opinions on these things, and that I hope you will all continue to weigh in whether you agree with me or not. On further reflection, I think I was perhaps unfair in some elements of my critique last week. But, I have been ill for the past while, and so I’ll just pretend that my condition impaired my judgment. Of course, I’m still a bit ill now, but we’ll try to avoid a repeat.

Today’s map was submitted by my colleague Tim Wallace, who is responsible for naming this blog. We work in a building that also houses the Arthur Robinson Map Library, which occasionally gives away unwanted materials. Tim found this one on the free map table:

Detail. Obtained from Robinson Map Library, August 2009.

The provenance is unknown – it’s printed on thin magazine paper with a torn edge, and the reverse side contains portions of two articles which don’t identify the publication, though the corner reads “September 1979.” On the off chance you happen to know where it comes from, please write to me at cartastrophic@gmail.com.

I found the logic behind the legend confusing for a good while until I noticed the numbers. It appears that we have a map here which shows seismic risk for various tectonic plate boundaries. Red is the highest seismic potential. A fine-grain black-and-white checkered pattern is the lowest. Peach and yellow are in-between. This seems to come up every week on this blog, but I’ll say it again: if you’re showing ordered data, like high-to-low seismic potential, use an ordered set of symbols (colors, in this case). This is one reason why the legend threw me. Areas marked “Plate motion subparallel to arc” are apparently of a moderate-to-low seismic potential. But, because of the fact that they use a checkerboard pattern, and because I hadn’t the damnedest what that phrase meant, I couldn’t tell that item #4 on the legend was part of a larger scheme. This is worse than just misuse of colors; patterns are being thrown in needlessly now, too.

I could, in fact, still be reading this whole legend wrong, and reflecting poorly on the institution that agreed to award me a bachelor’s degree a few years ago. Feel free to comment if you think you’ve got a more sensible interpretation than my idea of items 1-6 being part of an ordered scheme of seismic potential.

One final note on the colors/patterns: The legend does not explain what the white bands are.

On to the point features. The symbols for successful forecast (presumably explained in the article) and active volcano are overprinted directly on top of the other colors. Look again at the colored bands. The red or yellow appear no different when they are on land vs. on water. The printer simply put these colors directly onto the white paper. But look now at those two point symbols – notice how their color changes based on whether they’re sitting on land or water or on top of something else. The printer put purple ink on top of green or blue or whatever was already there, instead of leaving a white space, as they did for the bands. Not sure what happened there, though there may be a reasonable explanation that someone more familiar with late 1970s printing technology can give. It does make the points very hard to see in some areas – I originally counted four stars, but now I can find eight. It also means that the point features shown in the legend do not match the color found on the map.

I’m hoping the magazine article makes the meaning of the Tsunami symbol clearer. Is this map showing Tsunamis that happened in the last decade? Ones happening right now? Not sure.

Note that the legend refers to various filled areas as being “sites” of earthquakes. Why are these not point features? Earthquakes have an epicenter, and move more in a circular outward fashion than a wide lateral band fashion. There may be more going on, as far as data processing goes (and, again, I wish I had the article that accompanies this), but it’s perplexing. Maybe the author(s) went with bands because it’s easier to see the bands than to dig out information out of scattered points? I’ll not be too hard on this, because it’s more mysterious than bad, without information to help understand why the map author(s) may have done this.

There are exactly two labels on the main map: Oaxaca, and Gulf of Alaska. Maybe those are both significant in the article, but it seems very strange to see just those two. They should probably be set in different type, at least, so that Oaxaca doesn’t look like the name of a sea off the Mexican coast. As a general guideline, cities and bodies of water ought to look different. One of the reasons for labeling things is to help readers who don’t already know what or where these features are. It’s entirely possible that a reader out there actually did look at this and, never having heard of Oaxaca, thought it was a water feature.

A similar problem comes up in the inset. Mexico is set in the same type as Central America. Central America is not (and was not), last I knew, a country. I’m reasonably sure Mexico is, however. But look at how they’re labeled – as though the text symbols mean the same thing in each case: country. And, of course, the tectonic plates are also set in the same type as everything else. Perhaps the mapmaker had a sponsorship deal from the makers of the typeface (I am having trouble identifying exactly which it is, on account of the scan resolution looking at the actual physical document, it appears to be Helvetica). If you are a typeface designer and want to pay me more than I deserve to use your glyphs on my maps, please contact me.

The inset would be better off having some kind of marker to show where exactly it corresponds to on the main map. Perhaps this might explain why Mexico was labeled: to help the reader locate the inset.

The water on the inset is jarring -the white makes it stand out far too much, calling your eye away from the main map. Best make it blue.

Boy, sure would be nice to have a legend to explain what’s going on with the inset. Are those blue triangles historical volcanic eruptions, or maybe earthquakes? Maybe they’re places less interesting than the Cheese Factory. And what are the little round-ish zones drawn in blue, which makes them hard to notice?

If you run this map through a filter which simulates how it might look to a person with the common red-green color vision impairment, you may notice that the green for the land and the orange for seismic potential level 2 end up looking very similar, which is rather problematic if you want to know which areas are plain land, and which areas might kill you in an earthquake.

A final reiteration of the main caveat to these criticisms – the original context for the map is missing, and the magazine article which I hope accompanied it may have helped this whole thing make more sense, and explained some things which seem out of place.

One Nice Thing: Some may disagree with me and say it’s overgeneralized, but I kind of like the simplicity of the linework. I think it works here, giving it an accessible, non-technical aesthetic. Michigan is misshapen, but I’ll live.

Another Nice Thing: Tim thinks it has a nice Schoolhouse Rock sort of feeling to it. Which is another way of getting at what I was saying above.

Remember David Wilkins, former US ambassador to Canada? Well, if you do a Google search on him, this map from whitepages.com comes up near the top, showing the distribution of telephone directory listings matching his name:

Since they apparently generate these automatically for most any name, I thought of doing my own. But, I figured that I would take another opportunity to increase the fame and internet profile of Mr. Wilkins. Can’t pass that up.

The colors are certainly less than ideal – as with so many of the maps seen here, there’s a mismatch between an orderable data set (number of listings) and an un-orderable symbology (the colors chosen to represent those numbers). Though, I suppose one can see a weak progression in the colors, depending on your perspective. But it’s still far from a good match to the data. Running from a light to a dark blue would be perfect. It would also be more friendly to people with color vision impairments.

It would also be nice if I didn’t have to assume that white means zero listings, since it could also reasonably mean “no data available.” Troubling is the fact that some of the small states are filled in with white on the main map, but on the inset, where they are enlarged, they are given a color. The inset needs to be consistent with the main map – else it makes it harder to understand that the inset is, in fact, a zoomed-in version of the main map.

A sacrifice made with a classed choropleth map like this is that you lose some precision in getting the numbers off of it. Look at the states in light blue – they all have anywhere from 1 to 11 listings for “David Wilkins.” Grouping states like this is perfectly reasonable, to help reduce the number of colors used on the map and make it easier for someone to pick out one distinct color and match it to the legend. Some ambiguity is necessary as part of this process. But, look at Texas – the only state colored in dark red. It apparently has anywhere from 43 to 53 listings. It’s the only state in its class – why is the exact number not specified?

The classification scheme in general is a bit odd. There are a few big goals you want to try and go for when deciding how to group your states. One is to minimize intra-class differences – that is, keep the class sizes small. You don’t want a class that goes 1 to 11 listings, and one that goes 12 to 500 listings. The second one is way too broad. Another is to try and make each class roughly the same size, which this map has a problem with. There’s one state in the dark red class, two in the orange class, and twenty-five in the light blue class. A third goal for class breaks is to try and have class breaks that are relatively even in number – as an astute reader points out below, the class breaks change in size just a bit, though they’re roughly pretty even, so I think they hold up pretty well. There are a few other goals, but I’ll leave it at that. As you might expect, it’s hard to fulfill all the goals at once, but the severity of the difference between 1 red state and 25 light blue ones is still pretty bad. The two lowest classes cover most of the country, and the two upper classes cover only three states. It makes those three states stand out, but more than they should. There’s not a large, unusual, and worth-pointing-out difference between the upper and lower end states, to my mind.

These data should probably be normalized, as well. Consider Texas again: a lot of people named David Wilkins live there. This is probably because a lot of people live there in the first place – it’s one of the most populous states. More populated places will probably have more people named David Wilkins. Likewise, you can’t find anyone named David Wilkins in places like Wyoming or South Dakota, because approximately no one lives in those states. The pattern shown by this map is highly correlated to the population distribution of the United States. It does not show whether or not people from Texas are more likely than people from Wisconsin to be named David Wilkins. Instead of making a map of how many telephone listings there are in each state for David Wilkins, the author(s) should plot how many listings there are for David Wilkins per million inhabitants of the state. Then you would find out that Delaware has 8.1 listings for David Wilkins per million inhabitants, vs. only 2.2 for Texas. The name is also particularly popular in South Carolina, which state the Ambassador calls home.

I find it a bit odd that they have region names listed for New England and the Mid Atlantic, but not the rest of the country. Also, I was under the impression that Maine was part of New England.

One Nice Thing: Those inset maps to the right sure are handy.

With that, I will leave off today’s effort to make this blog the #1 item on a Google search for David Wilkins.

This one was brought to my attention by a reader, Eliana, who appeared particularly exasperated that this map won an award. It seems that the folks at KWL took first prize in the 2009 Map Gallery competition at GeoTec, which bills itself as the largest GIS conference in Canada. According to the GeoTec site, the winners were selected “based on overall appearance and effectiveness as maps.” So, this means they have to a) look good, and b) communicate spatial information clearly. Longtime readers may recall that one of these things is more important than the other. Though this is not to say that making your map look good is unnecessary, and in a competition like this, it’s a fair criterion for judging.

Let’s start at the legend – of the 8200 or so red spots on this map, each one encodes how much hydropower could feasibly be generated at that site. A red dot means < 1 megawatt, a red square is 1 – 10 megawatts, and a red triangle is > 10 megawatts. This is a non-orderable scheme – squares, circles, and triangles cannot be put into an inherent order. So, it doesn’t make sense to use different shapes for different numbers of megawatts — which can be put into order. Dots of different size or perhaps color brightness (but the same color hue – so, for example, a scheme from light blue to dark blue) would be more sensible here.

The other big problem with this scheme is that if you look at the map, you can’t pick out the squares from the circles from the triangles in most areas. They’re way too small to be able to tell which shape is which without staring or zooming way in, and even then it’s sometimes ambiguous. I will add the caveat that I don’t know how large this map was printed – it may be less of a problem if this thing is two or three feet across. And I’m not even sure if this map really needs to go into this much detail. It does a good job as it stands of showing the general distribution of hydropower sites, mostly clustered along the west of the province. If the authors want to add an extra level of information, about how much power might be generated at each site, their task becomes much harder, because now the dots have to be separate enough, and big enough, for people to be able to tell how they vary. And the reader cannot effectively do that, here.

Even if you could visually tell one shape from another, however, it would still be difficult to pick out the overall pattern of where the 1 megawatt sites are, and where the 10 megawatt sites are. Shape, as a visual means of encoding information, is weak in terms of what we call selectivity. It’s hard to select just one shape, and then try and find the distribution of only that shape. It’s much easier to do this sort of task with something like size – you can quickly see where the big dots are clustered and where the small ones are. A quick example:

Notice how easier it is to pick out the cluster of small squares near the center than it is to pick out the cluster of triangles near the center - size has better selectivity than shape.

Moving on from the dots, let’s consider a few other, lesser offenses. The labeling has poor contrast with the background, especially at Stewart and Port Hardy. Interestingly, some of the labels have been set in light-colored type, to better stand out against the water, thus demonstrating that the labeler was mindful of contrast issues. But not enough to make them legible against a mass of little red shapes.

Notice the white area in the northwest. That’s part of Alaska. It looks like it’s buried under an ice cap or something, given the color scheme and the fact that it’s flat, while the rest of the map shows terrain relief. I’ve never been to Alaska, so I suppose it could in fact bear a great resemblance to Antarctica. More of concern to me is the fact that the authors have possibly done one worse than the dreaded island effect. Instead of either showing British Columbia as an island with no surrounding land, or showing it in its geographic context, with the USA and other provinces around, the authors have chosen to include just one part of one of the surrounding areas. It looks very odd, and I think it would look better showing just the province, really.

Speaking of odd, it looks like someone has discovered the joy of the “glow” effect in the Adobe suite of graphic tools, because the entire coast of British Columbia is glowing white. Now, a glow effect can be a great addition to a map, but it would probably make more sense to do one a light blue one that looks like shallow coastal water, rather than giving the appearance that there’s been some sort of radioactive disaster off the Canadian Pacific coast.

Since this is a map about hydropower based on the flow of rivers, where are the rivers on this map? You can see a few here and there, in a very light blue, but the hydrography should really stand out more. Maybe not every single creek, but at least the major ones.

Finally, a note on the map projection. The authors appear to have kept the central meridian for this conic projection somewhere far east of the map area – say, around the center of Canada. For those readers who may be confused by what I just said, I will avoid giving an entire lesson on map projections. Instead, here’s a somewhat related way of thinking about it: Consider your average map of Canada, grabbed randomly from the Internet – the kind with the curved appearance to it. Doesn’t it look like the authors of the map above took BC from the far west end of one of these typical Canada maps, and didn’t bother to rotate it so that it wasn’t tilted clockwise anymore? If it’s the only thing on the map, BC should be centered so that it’s northern border has a shallow “U” shape, instead of curving downward only. The projection on this map just constantly reminds me of the fact that BC is at the far west end of Canada. Perhaps the authors wanted to keep that suggestion in my mind – “British Columbia: We’re way over here!” Might make a good provincial motto.

One Nice Thing: The terrain relief is not just a useless bit of decoration – it’s useful, because hydropower potential is affected by terrain. You can see the river valleys and everything (if not the actual rivers, unfortunately). So, the relief here is both a nice aesthetic component, and conveys information relevant to the topic at hand. A win-win.

Before I leave off, I’d like to thank all of you who have been writing in to me and submitting maps you have encountered. It’s a big help to have other eyes looking for these things. I may not end up using every submission, but I appreciate them nonetheless.

I was out bowling with some friends, and the bowling balls were color-coded by weight. 12lb was green, for example, 15lb purple, and yellow was 7 or 8lb, I believe. I immediately thought, “using color hue to encode weight is inappropriate here, as these are ordinal data! An orderable color scheme should be used, such as light to dark green!” This is how bad I have gotten, how deeply ingrained some of these things have become.

See, back in the 16th century, this guy invented a map projection that helped make it easy to navigate at sea. And, if you happen to be making a nautical chart of the North Sea, this is probably a good projection to use. If you’re making a map of roughly anything else*, it’s a terrible choice (though this doesn’t stop Google Maps from using it). It distorts sizes greatly as you move away from the equator. See Brazil? Brazil is four times larger than Greenland, in reality. On a Mercator, Greenland looks like it could eat Brazil. There are also political arguments against using it as well, on account of the fact that it makes Europe and North America look larger, relative to Africa and South America, than they really are. Anyway, point being, there are manyotherbetteroptions for a simple world thematic map.

*Yes, there are a few legitimate uses for Mercator, but this is definitely not one of them.

Colors: Looking for countries that fit in the first three categories (“Consistently upholds human rights” / “Significant protections and safeguards” / “Adequate safeguards against abuse”)? They’re not on this map. Sorry, thanks for playing along with our legend! What there is, though, is Greece. Which is shaded a color that doesn’t actually appear in the legend. If you click on the picture you can see the table with the scores each country was given, and it’s clear there that Greece was supposed to be in the third-lowest category.

When you’re ranking countries according to a particular data set, such as how surveillance-y they are, you want to use colors that are likewise ranked, to visually show that these places can be ordered from most to least. Look quickly at North and South America and tell me, between Canada, Brazil, and the US, which is worse? It’s pretty hard to see any sort of natural arrangement there. Brazil is in red. Red is danger, right? But maybe the black indicates the dark and insidious police state that is the US. My favorite, though, is the bright magenta in places like France and India. What’s a good color to use that indicates that something is worse than red-level, but not as bad as black-level surveillance? That is the answer that someone came up with. Today’s surveillance alert level is bright magenta.

Also, I’m being a bit generous in interpretation, because the magenta in the legend doesn’t match the magenta on the map. The reds don’t really match, either. So, if you’re keeping score at home, a total of two out of the seven colors in the legend actually appear on the map. And I didn’t check the yellow that closely.

Grey probably means no data. But it’s probably dangerous to make assumptions about what colors mean on this map.

One nice thing: The colors are set such that the worst offenders, in black, are one of the things that stand out the most. Though, they are tied visually with the fourth-worst offenders, in yellow.

(Someone here in my lab disagrees with me on the above – given that there is a visual tie, the black doesn’t stand out sufficiently)

One alternate nice thing: It’s nice that there are insets to help clarify cramped regions.